Sat.Feb 04, 2023

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Google rushes to launch its own ChatGPT-like technology soon

TechSpot

Google will release its chatbot technology to the general public in "the next weeks and months," according to the CEO. Google Search will leverage LaMDA (Language Model for Dialogue Applications), the company's in-house language model, to deliver "factual" and conversational results to queries. The tech giant is prepared to show.

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The problem with AI neural networks, and more predictions about the future of technology

GeekWire

Mark R. Anderson of Strategic News Service, the Future in Review Conferences and Pattern Computer. Popular methods of artificial intelligence have an “explainability problem” — the inability to see exactly what’s happening between input and output, and this challenge will prevent major new advances from neural networks. That’s one of the predictions for 2023 from Mark R.

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Compact custom version of Windows 11 released

TechSpot

This week, NTDEV released Tiny11, a version of Windows 11 that needs only around 8GB of your hard drive and can run on 2GB of RAM. It also removes Windows 11's somewhat demanding system requirements, but users should know it makes some steep sacrifices to slim down.

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Are quantum computers for real? So far, the uncertainty principle rules the day

GeekWire

The IonQ Forte quantum system is roughly the same size as a standard data center cabinet. (IonQ Photo) Do full-fledged quantum computers already exist, or will it be a decade before they come into being? Will they have to be the size of a football field? A data center cabinet? A microwave oven? It seems as if the more you talk to computer scientists involved in the quantum computing quest, the less certain the answers become.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.